Libya experienced a substantial increase in oil revenue as a result of increased oil prices during the period of the late 1970s and early 1980s, and again after 2000. Recent increases in oil production and the price of oil, and their positive and negative macroeconomic impacts upon key macroeconomic variables, are of considerable contemporary importance to an oil dependent economy such as that...

the goal of this research was prioritize effective financial factors on price stock in tehran stock exchange with using topsis method. based on, it was reviewed literature and interviews and specially questionnaire obtain, effective financial factors to analysis with emphasize on topsis technique. the results shown in the entire ratio price to income, historical event share, eps and return on a...

U sing daily data, this study examined asymmetric pass-through of Iran’s oil price to banking stock index in Tehran Stock Exchange at different time horizons. Based on the results, the coefficient of long-run pass-through of oil price to banking stock index was estimated to be 0.63. Furthermore, based on the short-term ARDL-CECM models, the relationship between the positive component...

Stock price prediction is an important and challenging problem in stock market analysis. Existing prediction methods either exploit autocorrelation of stock price and its correlation with the supply and demand of stock, or explore predictive indictors exogenous to stock market. In this paper, using transaction record of stocks with identifier of traders, we introduce an index to characterize ma...

In this paper we assess the role of capital-embodied technology shocks in explaining properties of the cross section of stock returns. Existing theories seem to disagree on the sign and magnitude of the price the market demands for bearing the risk of such shocks: while a negative price is necessary to justify the value premium or the cross-sectional predictability of returns by firm characteri...

modelling and forecasting stock market is a challenging task for economists and engineers since it has a dynamic structure and nonlinear characteristic. this nonlinearity affects the efficiency of the price characteristics. using an artificial neural network (ann) is a proper way to model this nonlinearity and it has been used successfully in one-step-ahead and multi-step-ahead prediction of di...

This paper describes the prediction scheme of stock price by using multiagent systems. Agents predict the stock price according to their strategies which is defined from technical and fundamental parameters such as some index related to the stock price, the currency exchange rate of the Japanese Yen (JPY) against the US Dollar and so on. Agents are randomly generated to construct population and...

Stock prices in each industry are one of the major issues in the stock market. Given the increasing number of shareholders in the stock market and their attention to the price of different stocks in transactions, the prediction of the stock price trend has become significant. Many people use the share price movement process when com-paring different stocks while investing, and also want to pred...